• Journal of Environmental Impact Assessment
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• v.17 no.1
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• pp.47-56
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• 2008

Total Maximum Daily Load(TMDL) is a core basin management system to assign total emissions of pollutants to unit basin and emission source within a limit of the target water quality and to secure sustainability. considering "Environment and development" together. By current technical guidance of TMDL, the water quality in the riverbed of which the target water quality is noticed, must achieve the target; and the water quality standard for evaluating achievement of the target should be prescribed as non-excessive probability quality of water on the basis of the pertinent water quality documents. Therefore, the study calculated the target water quality by each unit basin which the target water quality must be noticed through the analysis of probability for water quality documents in rivers at the time of establishing a plan, and the study evaluated the achievement possibility of the target water quality by analyzing and comparing the target water quality plan with the standard water quality to evaluate the achievement of the target water quality. As the result, applying the proposed method to Mihocheon River system, it is concluded that selected the target water quality (Each BOD 3.3mg/1 and BOD 3.0mg/1) in Miho A and Musim A is available. Of course, it showed that the target water quality: BOD 2.5mg/1 in Miho A and BOD 3.0mg/1 in Musim A, could be achieved if the small reduction in B unit area was implemented.

• Advances in nano research
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• v.12 no.5
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• pp.529-547
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• 2022

Graphene is one of the strongest, stiffest, and lightest nanoscale materials known to date, making it a potentially viable and attractive candidate for developing lightweight structural composites to prevent high-velocity ballistic impact, as commonly encountered in defense and space sectors. In-plane twist in bilayer graphene has recently revealed unprecedented electronic properties like superconductivity, which has now started attracting the attention for other multi-physical properties of such twisted structures. For example, the latest studies show that twisting can enhance the strength and stiffness of graphene by many folds, which in turn creates a strong rationale for their prospective exploitation in high-velocity impact. The present article investigates the ballistic performance of twisted bilayer graphene (tBLG) nanostructures. We have employed molecular dynamics (MD) simulations, augmented further by coupling gaussian process-based machine learning, for the nanoscale characterization of various tBLG structures with varying relative rotation angle (RRA). Spherical diamond impactors (with a diameter of 25Å) are enforced with high initial velocity (V_i) in the range of 1 km/s to 6.5 km/s to observe the ballistic performance of tBLG nanostructures. The specific penetration energy (E_p^*) of the impacted nanostructures and residual velocity (V_r) of the impactor are considered as the quantities of interest, wherein the effect of stochastic system parameters is computationally captured based on an efficient Gaussian process regression (GPR) based Monte Carlo simulation approach. A data-driven sensitivity analysis is carried out to quantify the relative importance of different critical system parameters. As an integral part of this study, we have deterministically investigated the resonant behaviour of graphene nanostructures, wherein the high-velocity impact is used as the initial actuation mechanism. The comprehensive dynamic investigation of bilayer graphene under the ballistic impact, as presented in this paper including the effect of twisting and random disorder for their prospective exploitation, would lead to the development of improved impact-resistant lightweight materials.

• Smart Structures and Systems
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• v.29 no.4
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• pp.641-652
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• 2022

High-rise structures prone to large vibrations under the action of strong winds, resulting in fatigue damage of the structural components and the foundation. A novel compound damping cable system (CDCS) is proposed to suppress the excessive vibrations. CDCS uses tailored double cable system with increased tensile stiffness as the connecting device, and makes use of the relative motion between the high-rise structure and the ground to drive the damper to move back-and-forth, dissipating the vibration mechanical energy of the high-rise structure so as to decaying the excessive vibration. Firstly, a third-order differential equation for the free vibration of high-rise structure with CDCS is established, and its closed form solution is obtained by the root formulas of cubic equation (Shengjin's formulas). Secondly, the analytical solution is validated by a laboratory model experiment. Thirdly, parametric analysis is conducted to investigate how the parameters affect the vibration control performance. Finally, the dynamic responses of the high-rise structure with CDCS under harmonic and stochastic excitations are calculated and its vibration mitigation performance is further evaluated. The results show that the CDCS can provide a large equivalent additional damping ratio for the vibrating structures, thus suppressing the excessive vibration effectively. It is anticipated that the CDCS can be used as a good alternative energy dissipation system for vibration control of high-rise structures.

• Earthquakes and Structures
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• v.14 no.5
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• pp.425-436
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• 2018

The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.2
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• pp.155-163
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• 1989

For a one link flexible arm control, quadratic optimal control is applied to the dynamic modilling which is derived from an assumed mode method. For the quadratic optimal control technique, the full state feedback must be obtained for closing the control loop, but because some of the states in the flexible system(e.g. the rate of change of the time dependent variables of the mode shapes) can not be directly measured, state estimator is necessary to achieve the practical implementation of the optimal controller. When disturbances and measurement noise occur, stochastic approach must be applied to estimating the states of the system. Kalman Filter is used as a stste estimator. Through the simulation, the flexible system with state estimator is compared with the flexible system assuming that all the states can be measured.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.76-85
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• 2022

One of the most fundamental challenges when designing controllers for dynamic systems is the adjustment of controller parameters. Usually the system model is used to get the initial controller, but eventually the controller parameters must be manually adjusted in the real system to achieve the best performance. To avoid this manual tuning step, data-driven methods such as machine learning were used. Recently, reinforcement learning became one alternative of this problem to be considered as an agent learns policies in large state space with trial-and-error Markov Decision Process (MDP) which is widely used in the field of robotics. However, on initial training step, as an agent tries to explore to the new state space with random action and acts directly on the controller parameters in real systems, MDP can lead the system safety-critical system failures. Therefore, the issue of 'safe exploration' became important. In this paper we meet 'safe exploration' condition with Control Barrier Function (CBF) which converts direct constraints on the state space to the implicit constraint of the control inputs. Given an initial low-performance controller, it automatically optimizes the parameters of the control law while ensuring safety by the CBF so that the agent can learn how to predict and control unknown and often stochastic environments. Simulation results on a quadrotor UAV indicate that the proposed method can safely optimize controller parameters quickly and automatically.

• Computational Structural Engineering
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• v.3 no.4
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• pp.143-148
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• 1990

The modal parameter estimations of linear multi-degree-of-freedom structural dynamic systems are carried out in time domain. For this purpose, the equation of motion is transformed into the auto regressive and moving average model with auxiliary stochastic input(ARMAX) model. The parameters of the ARMAX model are estimated by using the sequential prediction error method. Then the modal parameters of the system are obtained thereafter. Experimental results are given for a 3-story budding model subject to ground exitations.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.106-118
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• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.812-815
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• 1996

In this paper, we consider the optimal control problem based on Discrete Event Dynamic Systems(DEDS) in the Temporal Logic framework(TLF) which have studied for a convenient modeling technique. The TLF is enhanced with objective functions(event cost indices) and a measurement space is also defined. Our research goal is the design of the optimal controller for DEDSs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• Structural Engineering and Mechanics
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• v.23 no.6
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• pp.599-613
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• 2006

A method for the dynamical analysis of FE discretized uncertain linear and nonlinear structures is presented. This method is based on the moment equation approach, for which the differential equations governing the response first and second-order statistical moments must be solved. It is shown that they require the cross-moments between the response and the random variables characterizing the structural uncertainties, whose governing equations determine an infinite hierarchy. As a consequence, a closure scheme must be applied even if the structure is linear. In this sense the proposed approach is approximated even for the linear system. For nonlinear systems the closure schemes are also necessary in order to treat the nonlinearities. The complete set of equations obtained by this procedure is shown to be linear if the structure is linear. The application of this procedure to some simple examples has shown its high level of accuracy, if compared with other classical approaches, such as the perturbation method, even for low levels of closures.